A mixture model approach to spectral clustering and application to textual data
type: Item
instance of: scholarly article
title: A mixture model approach to spectral clustering and application to textual data
author: Cinzia Di Nuzzo
author: Salvatore Ingrassia
published in: Statistical Methods and Applications
publication date: 2023-01-13T00:00:00Z
Mathematics Subject Classification ID: 62-XX
zbMATH DE Number: 7642320
zbMATH Keywords: spectral clustering
zbMATH Keywords: Gaussian mixture models
zbMATH Keywords: document classification
describes a project that uses: mclust
MaRDI profile type: Publication
full work available at URL: s10260-022-00635-4
OpenAlex ID: W4224287896
cites work: Model-Based Clustering, Discriminant Analysis, and Density Estimation
cites work: A review of robust clustering methods
cites work: Gaussian bandwidth selection for manifold learning and classification
cites work: Q4939994
cites work: Finite mixture models
cites work: A vector space model for automatic indexing
cites work: The geometry of kernelized spectral clustering
cites work: Deep mixtures of unigrams for uncovering topics in textual data
DOI: 10.1007/S10260-022-00635-4
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description: scientific article; zbMATH DE number 7642320